1. Field of the Invention
The present invention relates to an image correction method and apparatus, and more particularly, to an image correction method and apparatus which can enhance the performance of image correction without deteriorating the image quality.
2. Description of the Related Art
Information provided to users by image acquisition apparatuses, such as digital cameras, includes not only text information but also various content such as still images, moving images and sounds. Of various forms of multimedia information, moving images, in particular, are a basis for video-on-demand (VOD) or interactive services. Therefore, relevant standardization proposals are being actively studied.
With the development of digital electronic engineering technology, conventional analog data is being converted into digital data. Accordingly, techniques to process various digital image data have been introduced to efficiently handle a huge amount of data. These digital image processing techniques have the following advantages.
First, when an analog image processing apparatus processes an analog signal, noise is inevitably added to the analog signal. Therefore, the deterioration of image quality cannot be avoided in the case of analog signals processed by the analog image processing apparatus. However, such deterioration of image quality does not occur when a digital image processing apparatus is used.
Second, since a signal is converted into a digital signal and processed accordingly, signal processing using a computer is possible. In other words, since an image signal is processed using a computer, various image processing operations, such as compressing image information, can be performed.
Currently, most of conventional digital image signal display apparatuses, such as liquid crystal displays (LCDs), plasma display panels (PDPs) and organic light emitting diodes (OLEDs), are adopting a red (R), green (G) and blue (B) color model.
A color model (or color space) is a method of representing the relationship between a color and other colors. Different image processing systems use different color models for different reasons. The RGB color model is composed of R, G and B, which are additive primary colors. Spectral elements of these primary colors are additionally combined to produce colors.
The RGB model is represented by a three-dimensional (3D) cube with R, G and B at edges of each axis. Black is located at the origin of the 3D cubic, and white is located at an opposite end of the 3D cubic. For example, in a 24-bit color graphic system having 8 bits per color channel, R is represented by (255,0,0).
The RGB model simplifies the design of computer graphic systems but is not ideal for all applications since there is a high correlation between R, G and B color components. Many image processing techniques, such as histogram equalization, process images using only the brightness thereof. Therefore, it is required to frequently convert an RGB image into a brightness image. In order to convert an RGB image to a grayscale image, a sum of the R, G and B color components respectively multiplied by ⅓, that is, a mean value of the R, G and B color components, may be used. However, the following equation may also be used according to a National Television Systems Committee (NTSC) standard.Y=0.288R+0.587G+0.114B  (1).
Technologies to improve image quality have been continuously studied as one of technological fields related to image representation techniques that are based on RGB sub-pixels. Conventional methods of improving image quality include adjusting the overall brightness of an image and performing histogram equalization.
If the overall brightness of an image is adjusted, the brightness of a dark area may be improved. However, since saturation occurs in a bright area, information is lost. In addition, although histogram equalization can be performed in a short period of time, the quality of an output image deteriorates after histogram equalization. A Retinex algorithm may also be used as another way to improve image quality. However, since a large-sized filter is needed to obtain an image of desired quality in the Retinex algorithm, the amount of calculation required increases.
In this regard, various inventions (for example, Korean Patent Publication No. 2004-080456, entitled “Method of Correcting Image Quality of Mobile Telecommunication Terminal with Built-in Camera”) have been suggested but still fail to solve the above problems.